code: def test_mfcc(device):
      x = example_y
      mfcc = MFCC(sr=example_sr).to(device)
      X = mfcc(torch.tensor(x, device=device).unsqueeze(0)).squeeze()
      X_librosa = librosa.feature.mfcc(x, sr=example_sr)
      assert np.allclose(X.cpu(), X_librosa, rtol=1e-3, atol=1e-2)
  
file_path: nnAudio/Installation/tests/tests_mel.py
imports: import pytest
  import librosa
  import torch
  from scipy.signal import chirp, sweep_poly
  import sys
  from nnAudio.Spectrogram import *
  from parameters import *
  import warnings
label_desc: Use image node_id 2 for calling a global function with example usage: test_mfcc(device) without return types